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\chapter{Background}

\paragraph{Infrasound Research} Infrasound is a low-frequency acoustic signal, inaudible to human ears. Its frequency is determined to be below 20\,Hz. The special characteristic of infrasound is the long-distance propagation. Depending to the source and frequency the range can be from a few meters to thousands of kilometers~\cite{infrasound}, by propagating through the atmosphere similar to long radio waves. Natural infrasonic sources are geological eruptions, volcanic explosions and earthquakes. Asteroids entering the earth atmosphere can be traced by sensitive infrasonic microphones. Even heavy fire and rain produces infrasound. Examples for man-made causes are aircrafts, rockets and any kind of explosion. 

While infrasound was accidently discovered 1883 by recording the pressure pulse of an eruption far away, the research infrasound began during the 1960'. The goal of the early research was the detection of nuclear explosions to watch the compliance of the international agreement for the usage of nuclear weapon. Later, arrays of infrasonic microphones are used to trace aircrafts and rockets by evaluating the coherent signal.

Since the 1990' the importance of infrasonic signals for the geophysics is increasing. As infrasound pervades even stone, underground explosions and eruptions are detectable by infrasonic antennas. The propagation speed through the air is slower than the speed for seismic waves (speed of sonic about 340\,$\frac{m}{s}$, speed of seismic primary waves between 5000 to 7000\,$\frac{m}{s}$). So, infrasound suits more to locate the source, because the time delay is easier to measure. Furthermore, the atmosphere is a homogeneous medium at short distances, what preserves the original signal. An eruption or explosion is categorized, differentiated by analyzing the infrasonic signal in order to generate \emph{fingerprints} of the event. 

Infrasonic sensors range from big and sensitive microphones and small microphones not bigger than a coin. The big one detect events located thousands of kilometers away. Of course, the small one are less sensitive, but have marginal power requirements. For instance a small and inexpensive electret condenser element microphone suits to be used with a wireless sensor node.


\paragraph{The Role of Wireless Sensor Networks} In spite of the mentioned opportunities and advantages of a WSN, established sensor deployments in the geophysical domain uses heavy and bulky measurement stations~\cite{harvard2}. The installation often requires vehicle or helicopter support. The deployments need high administrative efforts, especially if the data must be retrieved manually. So, in opposite to a WSN, the scale is very limited. 

However, assisting a geophysical study by a WSN has its challenges. For a useful analytical data evaluation the high fidelity of the data must be assured. The loss of a single data fragment can make a complete data record useless. Considering the demands for a stable sampling frequency and for accurate time stamps of the data records, the sensor nodes need to be time synchronized. Time synchronization can bring up complex and sophisticated approaches even under support of GPS devices. Other methods base on network time protocols.

Anyhow, the application range of a WSN is limited by the detection of discrete events. Due to energy constraints, complete signals, for instance long-term trends, can not be transmitted continuously. The quality of the event detection algorithms running locally on the sensor nodes directly impact the energy consumption. 

Moreover, an investigation of the wave propagation requires wide node separations. As the current WSN research deals with dense networks, in the geophysical domain deployments of or no less sensor range intersections is the issue.    

\paragraph{Infrasound Signals from Earthquake and Explosions in Arequippa, Peru} The volcano Ubinas, close to the city Arequipa, is the most active volcano of Peru. The volcano is a subject of the infrasonic and seismic research of the Particle and Astroparticle Physics Group, KTH. They work in characterization of infrasonic and seismic signals from mining explosions, volcano eruptions and earthquakes. The signals are analyzed using wavelet transform together with ampligram and time scale spectrum.

Infrasonic and seismic data has been recorded for three weeks on January 2006 at University of San Agustin observatory station (ARE), Arequipa. Therefore, a single infrasound microphone, seismometers, and accelerometers are deployed. An earthquake occurred 19th of January measuring 3.8 on the Richter scale and a mining explosion was recorded. The explosion was caused by the copper mine Cerro Verde, 20\,km south to Arequipa. Unfortunately, the volcano Ubinas remained inactive.

A new deployment, now based on a WSN, is planned with the focus on infrasonic monitoring and localization of eruptions and explosions caused by eruptions and explosions of the volcano Ubinas. Six microphones will be placed close to the vent. Events will be recorded and transported to the ARE observatory. The engineering of the application is the subject of this work. 



\paragraph{Related Works} A wired array of five infrasonic microphones were used to monitor the activity of the multi-vent volcano Stromboli, Italy~\cite{stromboli}. They were deployed in a distance of about 400\,m from the explosive craters. The array was installed in March 2003. The pre-amplified electret condenser microphones were connected by fiber optical cables with an internal spacing not more than 100\,m. Continuous signals were recorded centralized by a 16\,bit acquisition system and transmitted analogical by a frequency division multiplexer (one band per microphone) to the Stromboli village. The array was powered by two 50\,Watt solar panels. The main purpose was to detect eruptions and map them to the vents. The installation was a time consuming and complex enterprise. For instance, the cables were burrowed 1 meter into the earth. Depending to frequency division multiplexer and the power requirements, it is a good example for a non scalable system. However, eruptions were detected remotely almost in real time and successfully mapped to the vents.

A high affinity exists to the project of a collaborating group of Harvard University, University of New Hampshire, and University of North Carolina. This group uses the first time a WSN together with infrasound microphones and seismometers for geophysical studies. The first of their two deployments took place for several days in July 2004 in the area of the volcano Tungurahua, central Ecuador~\cite{harvard1}. The small amount of sensors were based on the Mica2 node. They sampled the data by 102\,Hz, 10\,bit and transmitted them over a 9\,km wireless link to a remote base station. The deployment collected 54 hours of data including nine large explosions. For the time synchronization a single GPS receiver is used in combination with the \emph{Flooding Time Synchronization Protocol} (FTSP). The archived
accuracy was 10\,ms with an error of more than six milliseconds. The data transport was controlled by the remote base station. Therefore, a self-developed routing protocol, by name \emph{Fetch}, was implemented. Furthermore, they evaluated their self-made algorithm for a distributed event detection. Node autonomy was not the issue.

The second deployment~\cite{harvard2}, in August 2006, was a larger network of 14 sensor nodes with enhanced hardware capabilities (Moteiv TMote Sky wireless sensor node). The network ran over three weeks and captured 230 volcanic events. 

Altogether, they showed the possibility of the successfully usage of a WSN for a long-term monitoring.  

 
